1. Field
The present disclosure relates generally to training and/or configuring a neural network, such as a convolutional neural network (CNN).
2. Information
A neural network may be utilized for a variety of tasks, including computer vision tasks, such as image recognition and/or image classification, for example. However, building a neural network may involve complicated trial-and-error tasks, in which tens of millions of parameters, for example, may be generated and/or modified over an extensive period of time, such as several days, weeks, or longer. Additionally, training a neural network may entail supplying numerous training samples, such as captured digital image files, which may number into tens of millions, for example. Further, in some instances, a chosen neural network architecture, while suitable for particular applications, may be overly cumbersome or unwieldy if utilized for other applications. Selection of a neural network that is otherwise too complex for an application, for example, may unnecessarily increase processing and other resources which may be involved in implementation.
Reference is made in the following detailed description of the accompanying drawings, which form a part hereof, wherein like numerals may designate like parts throughout to indicate corresponding and/or analogous components. It will be appreciated that components illustrated in the figures have not necessarily been drawn to scale, such as for simplicity and/or clarity of illustration. For example, dimensions of some components may be exaggerated relative to other components. Further, it is to be understood that other embodiments may be utilized. Furthermore, structural and/or other changes may be made without departing from claimed subject matter. It should also be noted that directions and/or references, for example, up, down, top, bottom, and so on, may be used to facilitate discussion of drawings and/or are not intended to restrict application of claimed subject matter. Therefore, the following detailed description is not to be taken to limit claimed subject matter and/or equivalents.